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Record W2770929246 · doi:10.19173/irrodl.v18i7.2942

Faculty Perception of Openness and Attitude to Open Sharing at the Indian National Open University

2017· article· en· W2770929246 on OpenAlexvenueno aff
Santosh Panda, Sujata Santosh

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2017
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
Fundersnot available
KeywordsOpen educational resourcesOpenness to experienceOpen educationDistance educationScarcityOpen learningHigher educationPublic relationsPolitical scienceSociologyKnowledge managementEconomic growthPedagogyPsychologyTeaching methodComputer scienceEconomicsCooperative learning

Abstract

fetched live from OpenAlex

In the past decade, the educational scenario world over has significantly been impacted by open access and open education movements. The philosophy of openness and sharing forms the cornerstone of the open education movement. The distance education approaches, together with open educational resources (OER) and massive open online courses (MOOCs), are being used to serve the increasing educational needs of diverse communities. However, adoption of openness as a core value and as part of the institutional strategy still remains a challenge for academic institutions in general, and distance education institutions in particular, in developing countries like India. In this research study, the authors report an analysis of the perception of the faculty of the Indira Gandhi National Open University of India (IGNOU) about openness and their attitude towards sharing of resources in academic institutions. Data was collected through a structured questionnaire administered to the teachers and academics of IGNOU (N=69). The results indicated that: the faculty members valued sharing of resources in academic institutions; learning resources should be made available free of cost; there is a strong need for training on intellectual property rights, copyright, and creation and use of OER; and there should be an institutional policy on OER for its effective use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0090.020
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.176
GPT teacher head0.485
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2017
Admission routes1
Has abstractyes

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